Probabilistic graphical models (Record no. 51460)

MARC details
000 -LEADER
fixed length control field 01863cam a2200241 a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ISURa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 090227s2009 maua b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780262013192 (hardcover : alk. paper)
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title English Language
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519.5420285
Item number KOL
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Koller, Daphne
9 (RLIN) 72627
245 10 - TITLE STATEMENT
Title Probabilistic graphical models
Remainder of title principles and techniques
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Cambridge, MA
Name of publisher, distributor, etc MIT Press
Date of publication, distribution, etc 2009
300 ## - PHYSICAL DESCRIPTION
Extent xxi, 1231 p.
Dimensions 24 cm.
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Adaptive computation and machine learning.
9 (RLIN) 69132
500 ## - GENERAL NOTE
General note 1. Introduction --<br/>2. Foundations --<br/>I. Representation --<br/>3. Bayesian Network Representation --<br/>4. Undirected Graphical Models --<br/>5. Local Probabilistic Models --<br/>6. Template-Based Representations --<br/>7. Gaussian Network Models --<br/>8. Exponential Family --<br/>II. Inference --<br/>9. Exact Inference: Variable Elimination --<br/>10. Exact Inference: Clique Trees --<br/>11. Inference as Optimization --<br/>12. Particle-Based Approximate Inference --<br/>13. MAP Inference --<br/>14. Inference in Hybrid Networks --<br/>15. Inference in Temporal Models --<br/>III. Learning --<br/>16. Learning Graphical Models: Overview --<br/>17. Parameter Estimation --<br/>18. Structure Learning in Bayesian Networks --<br/>19. Partially Observed Data --<br/>20. Learning Undirected Models --<br/>IV. Actions and Decisions --<br/>21. Causality --<br/>22. Utilities and Decisions --<br/>23. Structured Decision Problems --<br/>24. Epilogue --<br/>A. Background Material.
520 ## - SUMMARY, ETC.
Summary, etc A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Graphical modeling (Statistics)
9 (RLIN) 72628
Topical term or geographic name as entry element Bayesian statistical decision theory
General subdivision Graphic methods.
9 (RLIN) 72629
Topical term or geographic name as entry element Modèles graphiques (Statistique)
9 (RLIN) 72630
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Friedman, Nir
9 (RLIN) 72631
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Lending Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Lending Collection Applied Sciences Library Applied Sciences Library Lending Section 20/06/2019 21550.00   519.5420285 KOL 112993 21/06/2019 21/06/2019 Lending Books
    Dewey Decimal Classification     Reference Collection Applied Sciences Library Applied Sciences Library Reference Section 20/06/2019 21550.00   519.5420285 KOL 112994 21/06/2019 21/06/2019 Sheduled Reference